Resilience to COVID-19-related stressors: Insights from emerging adults in a South African township
Bibliographic record
Abstract
There is widespread recognition that stressors related to Coronavirus Disease 2019 (COVID-19) jeopardize the development of emerging adults, more particularly those living in disadvantaged communities. What is less well understood is what might support emerging adult resilience to COVID-19-related stressors. In response, this article reports a 5-week qualitative study with 24 emerging adults (average age: 20) living in a South African township. Using digital diaries and repeated individual interviews, young people shared their lived experiences of later (i.e., month 4 and 7) lockdown-related challenges (i.e., contagion fears; livelihood threats; lives-on-hold) and how they managed these challenges. An inductive thematic analysis showed that personal and collective compliance, generous ways-of-being, and tolerance-facilitators enabled emerging adult resilience to said challenges. Importantly, these resilience-enablers drew on resources associated with multiple systems and reflected the situational and cultural context of the township in question. In short, supporting emerging adult resilience to COVID-19-related stressors will require contextually aligned, multisystemic responses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".